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Relational Databases. Week 13 LBSC 671 Creating Information Infrastructures. Databases. Database Collection of data, organized to support access Models some aspects of reality DataBase Management System (DBMS) Software to create and access databases Relational Algebra

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Relational databases

Relational Databases

Week 13

LBSC 671

Creating Information Infrastructures


  • Database

    • Collection of data, organized to support access

    • Models some aspects of reality

  • DataBase Management System (DBMS)

    • Software to create and access databases

  • Relational Algebra

    • Special-purpose programming language

Structured information
Structured Information

  • Field An “atomic” unit of data

    • number, string, true/false, …

  • Record A collection of related fields

  • Table A collection of related records

    • Each record is one row in the table

    • Each field is one column in the table

  • Primary Key The field that identifies a record

    • Values of a primary key must be unique

  • Database A collection of tables

A simple example
A Simple Example

primary key

Registrar example
Registrar Example

  • Which students are in which courses?

  • What do we need to know about the students?

    • first name, last name, email, department

  • What do we need to know about the courses?

    • course ID, description, enrolled students, grades

A flat file solution
A “Flat File” Solution

Discussion Topic

Why is this a bad approach?

Goals of normalization
Goals of “Normalization”

  • Save space

    • Save each fact only once

  • More rapid updates

    • Every fact only needs to be updated once

  • More rapid search

    • Finding something once is good enough

  • Avoid inconsistency

    • Changing data once changes it everywhere

Relational algebra
Relational Algebra

  • Tables represent “relations”

    • Course, course description

    • Name, email address, department

  • Named fields represent “attributes”

  • Each row in the table is called a “tuple”

    • The order of the rows is not important

  • Queries specify desired conditions

    • The DBMS then finds data that satisfies them

A normalized relational database
A Normalized Relational Database

Student Table

Department Table

Course Table

Enrollment Table

Approaches to normalization
Approaches to Normalization

  • For simple problems (like the homework)

    • Start with “binary relationships”

      • Pairs of fields that are related

    • Group together wherever possible

    • Add keys where necessary

  • For more complicated problems

    • Entity relationship modeling (LBSC 670)

Example of join

“Joined” Table

Example of Join

Student Table

Department Table

Problems with join
Problems with Join

  • Data modeling for join is complex

    • Useful to start with E-R modeling

  • Join are expensive to compute

    • Both in time and storage space

  • But it is joins that make databases relational

    • Projection and restriction also used in flat files

Some lingo
Some Lingo

  • “Primary Key” uniquely identifies a record

    • e.g. student ID in the student table

  • “Compound” primary key

    • Synthesize a primary key with a combination of fields

    • e.g., Student ID + Course ID in the enrollment table

  • “Foreign Key” is primary key in the other table

    • Note: it need not be unique in this table


New Table

SELECT Student ID, Department


New Table

WHEREDepartment ID = “HIST”

The select command
The SELECT Command

  • Project chooses columns

    • Based on their label

  • Restrict chooses rows

    • Based on their contents

      • e.g. department ID = “HIST”

  • These can be specified together

    • SELECT Student ID, Dept WHERE Dept = “History”

Restrict operators
Restrict Operators

  • Each SELECT contains a single WHERE

  • Numeric comparison

    <, >, =, <>, …

    • e.g., grade<80

  • Boolean operations

    • e.g., Name = “John” AND Dept <> “HIST”

  • Using microsoft access
    Using Microsoft Access

    • Create a database called M:\rides.mdb

      • File->New->Blank Database

    • Specify the fields (columns)

      • “Create a Table in Design View”

    • Fill in the records (rows)

      • Double-click on the icon for the table

    Creating fields
    Creating Fields

    • Enter field name

      • Must be unique, but only within the same table

    • Select field type from a menu

      • Use date/time for times

      • Use text for phone numbers

    • Designate primary key (right mouse button)

    • Save the table

      • That’s when you get to assign a table name

    Entering data
    Entering Data

    • Open the table

      • Double-click on the icon

    • Enter new data in the bottom row

      • A new (blank) bottom row will appear

    • Close the table

      • No need to “save” – data is stored automatically

    Building queries
    Building Queries

    • Copy ride.mdb to your M:\ drive

    • “Create Query in Design View”

      • In “Queries”

    • Choose two tables, Flight and Company

    • Pick each field you need using the menus

      • Unclick “show” to not project

      • Enter a criterion to “restrict”

    • Save, exit, and reselect to run the query

    Some details about access
    Some Details About Access

    • Joins are automatic if field names are same

      • Otherwise, drag a line between the fields

    • Sort order is easy to specify

      • Use the menu

    • Queries form the basis for reports

      • Reports give good control over layout

      • Use the report wizard - the formats are complex

    • Forms manage input better than raw tables

      • Invalid data can be identified when input

      • Graphics can be incorporated

    Entity relationship diagrams
    Entity-Relationship Diagrams

    • Graphical visualization of the data model

    • Entities are captured in boxes

    • Relationships are captured using arrows

    Registrar er diagram
    Registrar ER Diagram


    Student ID

    First name

    Last name








    associated with



    Course ID

    Course Name


    Department ID

    Department Name

    Getting started with e r modeling
    Getting Started with E-R Modeling

    • What questions must you answer?

    • What data is needed to generate the answers?

      • Entities

        • Attributes of those entities

      • Relationships

        • Nature of those relationships

    • How will the user interact with the system?

      • Relating the question to the available data

      • Expressing the answer in a useful form

    Components of e r diagrams
    Components of E-R Diagrams

    • Entities

      • Types

        • Subtypes (disjoint / overlapping)

      • Attributes

        • Mandatory / optional

      • Identifier

    • Relationships

      • Cardinality

      • Existence

      • Degree

    Types of relationships



    Types of Relationships


    Project team e r example
    Project Team E-R Example






















    Making tables from e r diagrams
    Making Tables from E-R Diagrams

    • Pick a primary key for each entity

    • Build the tables

      • One per entity

      • Plus one per M:M relationship

      • Choose terse but memorable table and field names

    • Check for parsimonious representation

      • Relational “normalization”

      • Redundant storage of computable values

    • Implement using a DBMS

    Normalized table structure
    Normalized Table Structure

    • Persons: id, fname, lname, userid, password

    • Contacts: id, ctype, cstring

    • Ctlabels: ctype, string

    • Students: id, team, mrole

    • Iroles: id, irole

    • Rlabels: role, string

    • Projects: team, client, pstring


    1NF: Single-valuedindivisible (atomic) attributes

    Split “Doug Oard” to two attributes as (“Doug”, “Oard”)

    Model M:M implement-role relationship with a table

    2NF: Attributes depend on complete primary key

    (id, impl-role, name)->(id, name)+(id, impl-role)

    3NF: Attributes depend directly on primary key

    (id, addr, city, state, zip)->(id, addr, zip)+(zip, city, state)

    4NF: Divide independent M:M tables

    (id, role, courses) -> (id, role) + (id, courses)

    5NF: Don’t enumerate derivable combinations


    A more complex er diagram
    A More Complex ER Diagram

    cadastral: a public record, survey, or map of the value, extent, and ownership of land as a basis of taxation.

    Source: US Dept. Interior Bureau of Land Management,Federal Geographic Data Committee Cadastral Subcommittee

    Database programming
    Database “Programming”

    • Natural language

      • Goal is ease of use

        • e.g., Show me the last names of students in CLIS

      • Ambiguity sometimes results in errors

    • Structured Query Language (SQL)

      • Consistent, unambiguous interface to any DBMS

      • Simple command structure:

        • e.g., SELECT Last name FROM Students WHERE Dept=CLIS

      • Useful standard for inter-process communications

    • Visual programming (e.g., Microsoft Access)

      • Unambiguous, and easier to learn than SQL

    Structured query language
    Structured Query Language

    DESCRIBE Flight;

    Structured query language1
    Structured Query Language

    SELECT * FROM Flight;

    Structured query language2
    Structured Query Language

    SELECT Company.CompanyName, Company.CompanyPhone, Flight.Origin, Flight.DepartureTime

    FROM Flight,Company

    WHERE Flight.CompanyName=Company.CompanyName

    AND Flight.AvailableSeats>3;

    Putting the pieces together
    Putting the Pieces Together


    SQL Query




    Web Server



    Why database generated pages
    Why Database-Generated Pages?

    • Remote access to a database

      • Client does not need the database software

    • Serve rapidly changing information

      • e.g., Airline reservation systems

    • Provide multiple “access points”

      • By subject, by date, by author, …

    • Record user responses in the database

    Issues to consider
    Issues to Consider

    • Benefits of Databases

      • Multiple views

      • Data reuse

      • Scalable

      • Access control

    • Costs of Databases

      • Formal modeling

      • Complex (learn, design, implement, debug)

      • Brittle (relies on multiple communicating servers)

      • Not crawlable

    Key ideas
    Key Ideas

    • Databases are a good choice when you have

      • Lots of data

      • A problem that contains inherent relationships

    • Design before you implement

    • Join is the most important concept

      • Project and restrict just remove undesired stuff

    Databases in the real world
    Databases in the Real World

    • Some typical database applications:

      • Banking (e.g., saving/checking accounts)

      • Trading (e.g., stocks)

      • Airline reservations

    • Characteristics:

      • Lots of data

      • Lots of concurrent access

      • Must have fast access

      • “Mission critical”

    Relational databases

    Caching servers: 15 million requests per second, 95% handled by memcache (15 TB of RAM)

    Database layer: 800 eight-core Linux servers running MySQL (40 TB user data)

    Source: Technology Review (July/August, 2008)

    Database integrity
    Database Integrity

    • Registrar database must be internally consistent

      • Enrolled students must have an entry in student table

      • Courses must have a name

    • What happens:

      • When a student withdraws from the university?

      • When a course is taken off the books?

    Integrity constraints
    Integrity Constraints

    • Conditions that must always be true

      • Specified when the database is designed

      • Checked when the database is modified

    • RDBMS ensures integrity constraints are respected

      • So database contents remain faithful to real world

      • Helps avoid data entry errors

    Referential integrity
    Referential Integrity

    • Foreign key values must exist in other table

      • If not, those records cannot be joined

    • Can be enforced when data is added

      • Associate a primary key with each foreign key

    • Helps avoid erroneous data

      • Only need to ensure data quality for primary keys


    • Thought experiment: You and your project partner are editing the same file…

      • Scenario 1: you both save it at the same time

      • Scenario 2: you save first, but before it’s done saving, your partner saves

    Whose changes survive?

    A) Yours B) Partner’s C) neither D) both E) ???

    Concurrency example
    Concurrency Example

    • Possible actions on a checking account

      • Deposit check (read balance, write new balance)

      • Cash check (read balance, write new balance)

    • Scenario:

      • Current balance: $500

      • You try to deposit a $50 check and someone tries to cash a $100 check at the same time

      • Possible sequences: (what happens in each case?)

    Deposit: read balance

    Deposit: write balance

    Cash: read balance

    Cash: write balance

    Deposit: read balance

    Cash: read balance

    Cash: write balance

    Deposit: write balance

    Deposit: read balance

    Cash: read balance

    Deposit: write balance

    Cash: write balance

    Database transactions
    Database Transactions

    • Transaction: sequence of grouped database actions

      • e.g., transfer $500 from checking to savings

    • “ACID” properties

      • Atomicity

        • All-or-nothing

      • Consistency

        • Each transaction must take the DB between consistent states.

      • Isolation:

        • Concurrent transactions must appear to run in isolation

      • Durability

        • Results of transactions must survive even if systems crash

    Making transactions
    Making Transactions

    • Idea: keep a log (history) of all actions carried out while executing transactions

      • Before a change is made to the database, the corresponding log entry is forced to a safe location

    • Recovering from a crash:

      • Effects of partially executed transactions are undone

      • Effects of committed transactions are redone

    the log

    Before you go
    Before You Go

    On a sheet of paper, answer the following (ungraded) question (no names, please):

    What was the muddiest point in today’s class?